Freeway Slope Stability Evaluation Based on Multi-level Fuzzy Neural Network
On the basis of introduced basic principle of fuzzy-artificial neural network,this article constructed a slope stability assessment index system with multi-level fuzzy neural network,and made detailed evaluation criterion according to the assessment characteristics of slope stability.Through introducing the basic principle of multi-level comprehensive assessment from fuzzy mathematics and artificial neural network theory,it overcomes the defect of difficult to be quantified in evaluation process of slope stability.Therefore,it can be better to deal with some uncertain problems occurred in the slope stability assessment process,and as much as possible to express all factors influencing slope stability really and objectively.We selected 20 single factor evaluation indexes to assess slope stability based on surveying the high slope stability in Mian county-Ningqiang county freeway section.It took normal distribution model function as a membership function to develop a program with the model of fuzzy neural network.Furthermore,we took 30 typical slope examples as training sample to conduct effectiveness test and feedback test for the program.After the precision requirement was met,we used the program to evaluate 21 high slope examples and compared the results with the ones solved by traditional mechanical methods.The coincidence degree by using two kinds of methods to assess the same slope stability is 76.2%.
Fuzzy artificial neural network Slope stability evaluation Mountainous freeway
Yankai WU Xiansong Sang Bin Niu
College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao, Shandong, China 266590
国际会议
厦门
英文
1700-1703
2012-01-04（万方平台首次上网日期，不代表论文的发表时间）